The explosion of IoT and wearable devices determined a rising attention toward energy harvesting as source for powering these systems. In this context, many applications cannot afford the presence of a battery because of size, weight, and cost issues. Therefore, due to the intermittent nature of ambient energy sources, these systems must be able to save and restore their state, in order to guarantee progress across power interruptions. In this work, we propose a specialized backup/restore controller that dynamically tracks the memory accesses during the execution of the program. The controller then commits the changes to a snapshot in a nonvolatile memory (NVM) when a power failure is detected. Our approach does not require complex hybrid memories and can be implemented with standard components. Results on a set of benchmarks show an average 8× reduction in backup size. Thanks to our dedicated controller, the backup time is further reduced by more than 100×, with an area and power overhead of only 0.4% and 0.8%, respectively, with respect to a low-end IoT node.

The following topics are dealt with: learning (artificial intelligence); neural nets; field programmable gate arrays; integrated circuit design; logic design; optimisation; network routing; low-power electronics; cryptography; electronic design automation.